The present invention generally relates to wireless communication devices, and particularly relates to iteratively calculating a channel response estimate for use in received signal processing.
Signals transmitted in a wireless communication system such as a Code Division Multiple Access (CDMA) or Wideband CDMA (WCDMA) system are subjected to multiple sources of interference and noise as they propagate via radio channels. The interference and noise components that affect signal transmission and reception in a wireless communication system are broadly referred to as impairments. Certain types of impairments may be correlated. That is, two seemingly independent signal impairments may in fact be related, and thus are said to be correlated. Some conventional receiver types such as a Generalized-RAKE (G-RAKE) receiver and its Chip Equalizer (CEQ) counterpart use knowledge of impairment correlations to improve received signal processing. G-RAKE receivers and CEQs also use an estimate of a multipath fading channel response in their received signal processing.
For example, a G-RAKE receiver includes various signal “fingers” where each finger has an assigned path delay for receiving a particular image of a multipath signal and a correlator for de-spreading the received image. In combination, the signal fingers de-spread multiple signal images of a received multipath signal, thus utilizing the multipath channel dispersion phenomenon. Additional “probing fingers” may be placed off path delays for capturing impairment correlations information. The finger outputs are weighted and coherently combined to improve received signal demodulation and/or received signal quality reception estimation, e.g., signal-to-interference (plus noise) (SIR) estimation. The processing weights assigned to the finger outputs are conventionally a function of the channel response and impairment correlations. As such, knowledge of signal impairments may be used to improve received signal processing. In a similar manner, CEQs utilize impairment correlations information for improving received signal processing where the selection of equalization filter taps in a CEQ is comparable to the placement of fingers in a G-RAKE receiver and the generation of equalization filter coefficients is comparable to the generation of G-RAKE combining weights.
Parametric G-RAKE receivers estimate impairment correlations using a modeling approach. The model employs parameters, sometimes referred to as fitting parameters, that can be estimated in a number of ways such as least-squares fitting. The parametric impairment correlations modeling process depends on corresponding model fitting parameters and on estimates of the channel response. However, signal impairments affect the channel response estimation process, particularly when the impairments are severe. As such, impairment correlation estimation and channel response estimation may be interdependent, particularly when interference is severe.